Dynamic RF Transmit Power Adaptation for Mobile Node Networks
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Solution Overview
Problem
Current communication networks are inadequate in supporting complex arrays of both moving and static nodes, such as those found in the Internet of Moving Things and autonomous vehicle networks, due to limitations in adaptability and efficiency.
Innovation Solution
A communication network architecture that is dynamically configurable, utilizing a platform that is always-on, responsive, robust, and scalable, with adaptive power management and flexible configuration to support both mobile and static nodes, enabling efficient connectivity and data management across various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current communication networks are used to support complex arrays of moving and static nodes, then basic connectivity is maintained, but adaptability and efficiency are insufficient
Solution Approach 1:
The system dynamically adapts transmit power levels based on real-time network conditions, node mobility, and traffic requirements. The network transitions from static configuration to dynamic reconfiguration, allowing nodes to adjust their operational parameters continuously to maintain optimal performance in changing environments.
Solution Approach 2:
The invention changes key operational parameters including transmit power levels, modulation schemes, and coding rates adaptively. By modifying these parameters based on channel conditions and network state, the system achieves both high adaptability to different scenarios and maintained efficiency through optimized parameter selection.
2Reliability
If transmit power is increased to improve communication reliability in mobile networks, then connectivity is enhanced, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts transmit power as a variable parameter based on channel conditions, distance, and traffic requirements. Instead of using fixed high power, the system optimizes power levels in real-time, achieving reliable connectivity only when necessary and reducing power consumption during favorable conditions.
Solution Approach 2:
The network implements feedback mechanisms where nodes report channel quality, received signal strength, and power consumption metrics. Based on this feedback, the system adjusts transmit power levels to maintain connectivity while minimizing energy usage, creating a closed-loop control system that balances reliability and efficiency.
3Device complexity
If the network supports both mobile and static nodes with fixed configuration, then device complexity is reduced, but adaptability to different environments deteriorates
Solution Approach 1:
The network configuration transitions from static to dynamic, allowing automatic adaptation to different environments. Nodes can seamlessly switch between mobile and static modes, and the network reconfigures routing, power levels, and resource allocation based on current environmental conditions without requiring complex manual configuration.
Solution Approach 2:
The system implements self-configuration and self-optimization capabilities where nodes automatically adjust their parameters based on local conditions and network state. This self-service approach eliminates the need for complex external configuration while maintaining high adaptability to different environments through autonomous decision-making.
Data Source
AI summary
Communication network architectures, systems and methods for supporting a network of mobile nodes. As a non-limiting example, various aspects of this disclosure provide communication network architectures, systems, and methods for supporting a dynamically configurable communication network comprising a complex array of both static and moving communication nodes (e.g., the Internet of moving things). For example, a communication network implemented in accordance with various aspects of the present disclosure may support transmission power adaptation in a network of moving things comprising various fixed nodes, mobile nodes, and/or a combination thereof, which are selectable to achieve any of a variety of system goals.